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000899107 019__ $$a1111789787$$a1114170475
000899107 020__ $$a9789811393143$$q(electronic book)
000899107 020__ $$a9811393141$$q(electronic book)
000899107 020__ $$z9811393133
000899107 020__ $$z9789811393136
000899107 0248_ $$a10.1007/978-981-13-9
000899107 035__ $$aSP(OCoLC)on1110267219
000899107 035__ $$aSP(OCoLC)1110267219$$z(OCoLC)1111789787$$z(OCoLC)1114170475
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000899107 049__ $$aISEA
000899107 050_4 $$aQA278.2$$b.P35 2019
000899107 08204 $$a519.5/36$$223
000899107 1001_ $$aPal, Manoranjan,$$eauthor.
000899107 24510 $$aApplications of regression techniques /$$cManoranjan Pal, Premananda Bharati.
000899107 264_1 $$aSingapore :$$bSpringer,$$c[2019]
000899107 300__ $$a1 online resource
000899107 336__ $$atext$$btxt$$2rdacontent
000899107 337__ $$acomputer$$bc$$2rdamedia
000899107 338__ $$aonline resource$$bcr$$2rdacarrier
000899107 504__ $$aIncludes bibliographical references.
000899107 5050_ $$aChapter 1: Introduction to Regression Analysis and an overview of the techniques used in the book -- Chapter 2: Regression Decomposition Technique towards Finding Intra-Household Gender Bias of Calorie Consumption -- Chapter 3: Estimation of Poverty Rates by Calorie Decomposition Method -- Chapter 4: Estimating Calorie-Poverty Rates through Regression -- Chapter 5: Contribution of Regressors: A Set Theoretic Approach -- Chapter 6: Estimation of Hidden Markov Chain through Regression -- Chapter 7: Finding Geometric Mean and Aggregate Growth Rate through regression -- Chapter 8: Summary and Discussions.
000899107 506__ $$aAccess limited to authorized users.
000899107 520__ $$aThis book discusses the need to carefully and prudently apply various regression techniques in order to obtain the full benefits. It also describes some of the techniques developed and used by the authors, presenting their innovative ideas regarding the formulation and estimation of regression decomposition models, hidden Markov chain, and the contribution of regressors in the set-theoretic approach, calorie poverty rate, and aggregate growth rate. Each of these techniques has applications that address a number of unanswered questions; for example, regression decomposition techniques reveal intra-household gender inequalities of consumption, intra-household allocation of resources and adult equivalent scales, while Hidden Markov chain models can forecast the results of future elections. Most of these procedures are presented using real-world data, and the techniques can be applied in other similar situations. Showing how difficult questions can be answered by developing simple models with simple interpretation of parameters, the book is a valuable resource for students and researchers in the field of model building.
000899107 588__ $$aDescription based on online resource; title from digital title page (viewed on August 26, 2019).
000899107 650_0 $$aRegression analysis.
000899107 7001_ $$aBharati, Premananda,$$eauthor.
000899107 77608 $$iPrint version: $$z9811393133$$z9789811393136$$w(OCoLC)1104044303
000899107 852__ $$bebk
000899107 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-13-9314-3$$zOnline Access$$91397441.1
000899107 909CO $$ooai:library.usi.edu:899107$$pGLOBAL_SET
000899107 980__ $$aEBOOK
000899107 980__ $$aBIB
000899107 982__ $$aEbook
000899107 983__ $$aOnline
000899107 994__ $$a92$$bISE